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EPH-MCP: Emergent Pattern Hunter

by psikosen
README.md5.27 kB
# 🕸️ EPH-MCP: Emergent Pattern Hunter **A revolutionary thinking architecture for LLMs via MCP (Model Context Protocol)** EPH-MCP transforms how AI systems reason by simulating the emergence of insights from interacting thought fragments, similar to how patterns arise in complex physical systems. ## Key Features - **Bottom-up Insight Emergence**: Instead of forcing conclusions, the insights just show up once all the pieces bounce around enough. - **Quantum-like Thought Dynamics**: Ideas overlap, collide, and stick together—sometimes they’re in two states at once until the picture clears. - **Multi-scale Pattern Detection**: We can spot the small stuff and the big picture at the same time—like zooming from street level to skyline. - **Contradiction as Feature**: Tension isn’t a bug, it’s fuel. Conflicts push the thinking somewhere new. - **Field-based Reasoning**: Everything plays out in this high-dimensional “idea space,” where concepts pull, push, and interact like a living grid. ## 🚀 Quick Start ### Installation ```bash # Clone the repository git clone https://github.com/yourusername/eph-mcp.git cd eph-mcp # Install dependencies pip install -r requirements.txt python -m spacy download en_core_web_sm # Quick test python quickstart.py ``` ### Basic Usage ### Start MCP Server ```bash python -m eph_mcp.server ``` The server will start on `localhost:3333` by default. ## How It Works EPH uses a 5-phase process: ### Phase 1: Thought Explosion First we blow up the question into a bunch of little sparks—50 to 150 fragments, each one a different angle or half-formed idea. We mix in every trick we’ve got: free association, “what if” games, parallel universes, quantum superposition vibes. Each fragment lands in some wild high-dimensional space, like confetti drifting around a cosmic dance floor. ### Phase 2: Interaction Dynamics Now those fragments start bumping into each other like charged particles. - Similar ones pull together. - Opposites push apart. - Some bind tightly, others spin off. It’s basically like running a mini-universe simulation where ideas collide until the system chills into something stable (simulated annealing). ### Phase 3: Pattern Detection From the chaos, we spot emergent shapes—like finding constellations in the stars: - Crystalline lattices → clean, regular structures - Strange attractors → looping chaos - Phase transitions → that “sudden click” when ideas reorganize - Soliton waves → insights that keep traveling without losing shape - …plus more funky forms ### Phase 4: Pattern Crystallization Here, the raw patterns solidify into actual insights. We check each one for: - Confidence (does it hold up?) - Novelty (is it fresh?) - Clarity (can you actually explain it to a friend?) We don’t force everything to agree—contradictions are saved too, like tension in a good story. ### Phase 5: Pattern Weaving Finally, we stitch the insights together into something you can actually use. Different ways to weave: - Convergent synthesis → pull it all into one neat answer - Dialectical → thesis + antithesis → synthesis - Narrative threading → tell it like a story, connecting the dots naturally ## 📊 Configuration Create a `config.json` file to customize behavior: ```json { "explosion": { "n_fragments": 100, "temperature": 1.5, "embedding_model": "all-MiniLM-L6-v2" }, "interaction": { "iterations": 150, "initial_temperature": 1.0, "cooling_rate": 0.995 }, "detection": { "min_pattern_size": 3, "pattern_threshold": 0.5 }, "crystallization": { "confidence_threshold": 0.5, "novelty_threshold": 0.3 }, "weaving": { "max_insights": 5, "coherence_threshold": 0.6 } } ``` ## 🛠️ MCP Tools The server exposes 4 main tools via MCP: ### `think_emergently` Main reasoning tool - applies full EPH process ```python { "query": "Your question here", "return_intermediate": false, "visualize": true } ``` ### `analyze_patterns` Analyze text for emergent patterns without full reasoning ```python { "text": "Text to analyze", "pattern_types": ["contradiction", "harmony"], "min_confidence": 0.5 } ``` ### `compare_thoughts` Compare multiple ideas for relationships ```python { "thoughts": ["idea 1", "idea 2", "idea 3"], "find_contradictions": true, "find_harmonies": true } ``` ### `reasoning_history` Access and analyze past reasoning sessions ```python { "last_n": 5, "analyze": true } ``` Enable with `visualization.enabled: true` in config. ## Testing Run the test suite: ```bash # Basic tests python tests/test_basic.py # Full test suite (if available) pytest tests/ ``` ## 📚 Examples Explore different reasoning scenarios: ```bash python examples/usage_examples.py ``` ## Contributing Contributions are welcome! Areas of interest: - New generation strategies for thought explosion - Alternative pattern detection algorithms - Visualization improvements - Performance optimization - Integration with other MCP tools ## Acknowledgments - Inspired by physics and emergent systems *"In the dance of fragments, meaning emerges"* - EPH Philosophy

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